Search NASA⌕ Search

SEARCH · Search NASA

Results for “Estimation method”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Trade-Wind Cloudiness and Climate

Closed Mesoscale Cellular Convection (MCC) consists of mesoscale cloud patches separated by narrow clear regions. Strong radiative cooling occurs at the cloud top. A dry two-dimensional Bousinesq model is used to study the effects of cloud-top cooling on convection. Wide updrafts and narrow downdrafts are used to indicate the asymmetric circulations associated with the mesoscale cloud patches. Based on the numerical results, a conceptual model was constructed to suggest a mechanism for the formation of closed MCC over cool ocean surfaces. A new method to estimate the radioative and evaporative cooling in the entrainment layer of a stratocumulus-topped boundary layer has been developed. The method was applied to a set of Large-Eddy Simulation (LES) results and to a set of tethered-balloon data obtained during FIRE. We developed a statocumulus-capped marine mixed layer model which includes a parameterization of drizzle based on the use of a predicted Cloud Condensation Nuclei (CCN) number concentration. We have developed, implemented, and tested a very elaborate new stratiform cloudiness parameterization for use in GCMs. Finally, we have developed a new, mechanistic parameterization of the effects of cloud-top cooling on the entrainment rate.

Randall, David A.↗
NASA NTRS2016

Supplement: The Rate of Binary Black Hole Mergers Inferred from Advanced LIGO Observations Surrounding GW150914

This article provides supplemental information for a Letter reporting the rate of (BBH) coalescences inferred from 16 days of coincident Advanced LIGO observations surrounding the transient (GW) signal GW150914. In that work wereported various rate estimates whose 90% confidence intervals fell in the range 2600 Gpc(exp -3) yr(exp -1). Here we givedetails on our method and computations, including information about our search pipelines, a derivation of ourlikelihood function for the analysis, a description of the astrophysical search trigger distribution expected frommerging BBHs, details on our computational methods, a description of the effects and our model for calibrationuncertainty, and an analytic method for estimating our detector sensitivity, which is calibrated to our measurements.

gravitational waves – stars: black holes↗
DOE OSTI2024

Qualitative and Quantitative Evaluation for Representative Human Reliability Analysis Methods

The Korea Institute of Nuclear Safety (KINS) is the regulatory expert organization established by the Korean government to strengthen the nation’s technical capabilities relating to nuclear safety regulation. KINS oversees the technical aspects of nuclear safety regulation, including safety reviews, inspections, education, and safety research—all conducted based on technical knowledge and accumulated regulatory experience. In 2023, KINS requested that Idaho National Laboratory (INL) validates representative human reliability analysis (HRA) methods used throughout the world, thus affording KINS with a basis for determining an HRA method adequate for its domestic regulatory purposes. The present paper mainly examines INL’s efforts in this regard. The resulting INL study covered four representative HRA methods widely used by nuclear utilities and regulatory institutes. These methods were qualitatively evaluated by applying specific evaluation criteria and determining how well each method reflected critical HRA issues. For this assessment, INL benchmarked the Halden International HRA Empirical Study. Using the Halden empirical data, along with information on human failure events (HFEs), the present study employed the selected HRA methods to estimate human error probabilities (HEPs) for the HFEs. It also performed statistical analyses to compare the HEPs predicted via the HRA methods against those from the Halden empirical data.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

The Davis–Chandrasekhar–Fermi method revisited

ABSTRACT Despite the rich observational results on interstellar magnetic fields in star-forming regions, it is still unclear how dynamically significant the magnetic fields are at varying physical scales, because direct measurement of the field strength is observationally difficult. The Davis–Chandrasekhar–Fermi (DCF) method has been the most commonly used method to estimate the magnetic field strength from polarization data. It is based on the assumption that gas turbulent motion is the driving source of field distortion via linear Alfvén waves. In this work, using MHD simulations of star-forming clouds, we test the validity of the assumption underlying the DCF method by examining its accuracy in the real 3D space. Our results suggest that the DCF relation between turbulent kinetic energy and magnetic energy fluctuation should be treated as a statistical result instead of a local property. We then develop and investigate several modifications to the original DCF method using synthetic observations, and propose new recipes to improve the accuracy of DCF-derived magnetic field strength. We further note that the biggest uncertainty in the DCF analysis may come from the linewidth measurement instead of the polarization observation, especially since the line-of-sight gas velocity can be used to estimate the gas volume density, another critical parameter in the DCF method.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1990

Modeling of solar oscillation power spectra

To produce accurate estimates of the line-profile parameters of a model used to represent the spectral features in a solar oscillation power spectrum, it is necessary to (1) select the appropriate probability density function when deriving the maximum-likelihood function to be employed for the parameter estimation and (2) allow for the redistribution of spectral power caused by gaps in the data string. This paper describes a maximum-likelihood method for estimating the model parameters (based on the observed power spectrum statistics) that accounts for redistribution of spectral power caused by gaps in the data string, by convolving the model with the power spectrum of the observed window function. The accuracy and reliability of the method were tested using both artificial and authentic solar oscillation power spectrum data. A comparison of this method with various least-squares techniques is also presented.

Anderson, Edwin R.↗
DOE OSTI2023

Measuring photometric redshifts for high-redshift radio source surveys

With the advent of deep, all-sky radio surveys, the need for ancillary data to make the most of the new, high-quality radio data from surveys like the Evolutionary Map of the Universe (EMU), GaLactic and Extragalactic All-sky Murchison Widefield Array survey eXtended, Very Large Array Sky Survey, and LOFAR Two-metre Sky Survey is growing rapidly. Radio surveys produce significant numbers of Active Galactic Nuclei (AGNs) and have a significantly higher average redshift when compared with optical and infrared all-sky surveys. Thus, traditional methods of estimating redshift are challenged, with spectroscopic surveys not reaching the redshift depth of radio surveys, and AGNs making it difficult for template fitting methods to accurately model the source. Machine Learning (ML) methods have been used, but efforts have typically been directed towards optically selected samples, or samples at significantly lower redshift than expected from upcoming radio surveys. This work compiles and homogenises a radio-selected dataset from both the northern hemisphere (making use of Sloan Digital Sky Survey optical photometry) and southern hemisphere (making use of Dark Energy Survey optical photometry). We then test commonly used ML algorithms such as k-Nearest Neighbours (kNN), Random Forest, ANNz, and GPz on this monolithic radio-selected sample. We show that kNN has the lowest percentage of catastrophic outliers, providing the best match for the majority of science cases in the EMU survey. We note that the wider redshift range of the combined dataset used allows for estimation of sources up to z = 3 before random scatter begins to dominate. When binning the data into redshift bins and treating the problem as a classification problem, we are able to correctly identify ≈ 76% of the highest redshift sources—sources at redshift z > 2.51 —as being in either the highest bin (z > 2.51) or second highest (z = 2.25).

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2006

Attenuating Stereo Pixel-Locking via Affine Window Adaptation

For real-time stereo vision systems, the standard method for estimating sub-pixel stereo disparity given an initial integer disparity map involves fitting parabolas to a matching cost function aggregated over rectangular windows. This results in a phenomenon known as 'pixel-locking,' which produces artificially-peaked histograms of sub-pixel disparity. These peaks correspond to the introduction of erroneous ripples or waves in the 3D reconstruction of truly Rat surfaces. Since stereo vision is a common input modality for autonomous vehicles, these inaccuracies can pose a problem for safe, reliable navigation. This paper proposes a new method for sub-pixel stereo disparity estimation, based on ideas from Lucas-Kanade tracking and optical flow, which substantially reduces the pixel-locking effect. In addition, it has the ability to correct much larger initial disparity errors than previous approaches and is more general as it applies not only to the ground plane.

pixel locking effect↗
DOE OSTI2025

Mapping tree height in complex terrain of northern China using ultra-high-resolution images

Tree height is a key parameter for estimating forest biomass and carbon sequestration. In recent years, notable progress has been made in mapping tree height using satellite imagery. However, existing tree height products show low accuracy in mountainous and complex terrains, and few studies typically addressed tree height estimations in mountain areas. This study examines the Mentougou district of Beijing, China, characterized by complex terrain and mountainous landscapes. We analyzed two methods for estimating tree height: one using only spectral features and another combining spectral features with topographic factors (elevation, slope, aspect). We used 3-m resolution PlanetScope 8-band multispectral imagery, with 710 field-measured individual tree heights averaged to obtain 471 pixel-level tree height values as ground-truth, to develop tree height prediction models using eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Gradient Boosting Machine (GBM) models. The results show that the XGBoost model consistently presented the highest accuracy for both methods evaluated. Specifically, the XGBoost model that combined spectral data with elevation and slope variables with an R² of 0.75 and an RMSE of 2.69 m. Using the XGBoost model, we generated the tree height map for the Mentougou area at 3 m resolution, showing tree heights ranging from 0.5 to 30.4 m, and the model’s prediction error standard deviations ranged from 2.50 to 4.71 m, indicating reliable performance across varied terrain. Additionally, we compared and evaluated the global tree height products, identifying limitations in the accuracy within complex terrains. This study demonstrates the potential for accurately predicting tree heights by combining high-resolution multispectral satellites with a terrain factor modeling approach.

Complex terrain↗
DOE OSTI2020

Physically based correction of systematic errors of Rotating Shadowband Irradiometers

Accurate measurements of direct normal, diffuse horizontal and global horizontal irradiance (DNI, DHI and GHI) are needed for meteorological studies and are essential for the solar resource assessment at potential solar power plant sites. Often, these potential sites are remote and hence require robust sensors that require minimal maintenance that are not affected strongly by soiling. Therefore, Rotating Shadowband Irradiometers (RSI) are widely used for resource assessment. To achieve the required accuracy, corrections for the raw values of RSIs depending on systematic temperature, incidence angle and spectral errors must be used, and a thorough calibration of the sensor head must be applied. The existing correction functions are derived from comparisons of RSIs to thermopile radiometers at selected sites and therefore empirical. Their accuracy is considered to be site dependent. In this work a new correction and calibration method is presented that removes the systematic errors using a physical approach. It is based on information of the sensor properties as well as measurements of its directional response, and incorporates the atmospheric conditions at the measurement site. In this case, no empiric relations obtained from a specific site are required. The method requires estimates of the current DHI and GHI spectra during each measurement of the RSI. Based on these spectra, a spectral correction, which includes a spectrum dependent temperature correction, can be made without employing empirical relationships. The new physical calibration and correction method is tested at three sites and reaches similar results compared to the empirical functions. This is already achieved with rudimentary estimations of the GHI and DHI spectra and we expect that these estimations can be improved in the future. The results indicate that the physical approach reduces the problematic location dependence of the current calibration and correction methods. The physical correction and calibration method show promise for a further improvement of the RSI accuracy.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Detecting outbreaks using a spatial latent field

In this paper, we present a method for estimating the infection-rate of a disease as a spatial-temporal field. Our data comprises time-series case-counts of symptomatic patients in various areal units of a region. We extend an epidemiological model, originally designed for a single areal unit, to accommodate multiple units. The field estimation is framed within a Bayesian context, utilizing a parameterized Gaussian random field as a spatial prior. We apply an adaptive Markov chain Monte Carlo method to sample the posterior distribution of the model parameters condition on COVID-19 case-count data from three adjacent counties in New Mexico, USA. Our results suggest that the correlation between epidemiological dynamics in neighboring regions helps regularize estimations in areas with high variance (i.e., poor quality) data. Using the calibrated epidemic model, we forecast the infection-rate over each areal unit and develop a simple anomaly detector to signal new epidemic waves. Our findings show that anomaly detector based on estimated infection-rates outperforms a conventional algorithm that relies solely on case-counts.

Safta, Cosmin [Sandia National Laboratories (SNL-C↗
DOE OSTI2016

SUPPLEMENT: “THE RATE OF BINARY BLACK HOLE MERGERS INFERRED FROM ADVANCED LIGO OBSERVATIONS SURROUNDING GW150914” (2016, ApJL, 833, L1)

This article provides supplemental information for a Letter reporting the rate of (BBH) coalescences inferred from 16 days of coincident Advanced LIGO observations surrounding the transient (GW) signal GW150914. In that work we reported various rate estimates whose 90% confidence intervals fell in the range 2–600 Gpc{sup −3} yr{sup −1}. Here we give details on our method and computations, including information about our search pipelines, a derivation of our likelihood function for the analysis, a description of the astrophysical search trigger distribution expected from merging BBHs, details on our computational methods, a description of the effects and our model for calibration uncertainty, and an analytic method for estimating our detector sensitivity, which is calibrated to our measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Soil moisture estimation using tomographic ground penetrating radar in a MCMC–Bayesian framework

In this paper, we focus on a hydrogeological inverse problem specifically targeting monitoring soil moisture variations using tomographic ground penetrating radar (GPR) travel time data. Technical challenges exist in the inversion of GPR tomographic data for handling non-uniqueness, nonlinearity and high-dimensionality of unknowns. We have developed a new method for estimating soil moisture fields from crosshole GPR data. It uses a pilot-point method to provide a low-dimensional representation of the relative dielectric permittivity field of the soil, which is the primary object of inference: the field can be converted to soil moisture using a petrophysical model. We integrate a multi-chain Markov chain Monte Carlo (MCMC)–Bayesian inversion framework with the pilot point concept, a curved-ray GPR travel time model, and a sequential Gaussian simulation algorithm, for estimating the dielectric permittivity at pilot point locations distributed within the tomogram, as well as the corresponding geostatistical parameters (i.e., spatial correlation range). We infer the dielectric permittivity as a probability density function, thus capturing the uncertainty in the inference. The multi-chain MCMC enables addressing high-dimensional inverse problems as required in the inversion setup. The method is scalable in terms of number of chains and processors, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. The proposed inversion approach can successfully approximate the posterior density distributions of the pilot points, and capture the true values. The computational efficiency, accuracy, and convergence behaviors of the inversion approach were also systematically evaluated, by comparing the inversion results obtained with different levels of noises in the observations, increased observational data, as well as increased number of pilot points.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A verification study of fatigue-based methods in API RP 1183 for estimating fatigue life of pipeline dents

Pipeline dents are mechanical damage caused by a third party in buried pipelines during construction or maintenance repair. Dents are recognized as a leading cause of pipeline failures for both liquid and gas transmission lines, and their assessment and management are critical to pipeline integrity. To meet the industry need, American Institute of Petroleum (API) in 2020 published a recommended practice (RP) 1183 – Assessment and Management of Pipeline Dents. This API code provides the pipeline industry “standard methods” for evaluating severity and fatigue life of pipeline dents with a single peak. This paper performed an initial verification study of fatigue-based methods prescribed in API RP 1183 for estimating fatigue life of pipeline dents. A brief review was first given to the dent fatigue-based methods, including three dent screening methods for estimating dent fatigue life in Sections 7.4.1, 7.4.2, and 7.4.3 of API 1183 and one dent assessment method for predicting fatigue life in Section 8.3.4. In order to verify these fatigue life prediction methods, a set of “standard examples” of dents provided in Annexes A.1 to A.5 of API RP 1183 were utilized in this study to calculate fatigue life, to determine restraint condition, and to evaluate both screening and assessment methods for single-peak dents. Through detailed calculations and comparisons, this study confirmed some specifications of API RP 1183, but also found some self-inconsistences and errors existing in this new API code. Furthermore, this includes the self-inconsistences between three screening methods and the self-inconsistence between the screening and assessment methods. On this basis, recommendations were made on how the operators should use API RP 1183, and what actions API should take to improve this code.

42 ENGINEERING↗
DOE OSTI2022

Analytical methods for superresolution dislocation identification in dark-field X-ray microscopy

In this work, we develop several inference methods to estimate the position of dislocations from images generated using dark-field X-ray microscopy (DFXM)—achieving superresolution accuracy and principled uncertainty quantification. Using the framework of Bayesian inference, we incorporate models of the DFXM contrast mechanism and detector measurement noise, along with initial position estimates, into a statistical model coupling DFXM images with the dislocation position of interest. We motivate several position estimation and uncertainty quantification algorithms based on this model. We then demonstrate the accuracy of our primary estimation algorithm on synthetic realistic DFXM images of edge dislocations in single-crystal aluminum. We conclude with a discussion of our methods’ impact on future dislocation studies and possible future research avenues.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Cold Molecular Gas Along the Merger Sequence in Local Luminous Infrared Galaxies

We present an initial result from the {sup 12}CO (J = 1–0) survey of 79 galaxies in 62 local luminous and ultraluminous infrared galaxy (LIRG and ULIRG) systems obtained using the 45 m telescope at the Nobeyama Radio Observatory. This is a systematic {sup 12}CO (J = 1–0) survey of the Great Observatories All-sky LIRGs Survey (GOALS) sample. The molecular gas mass of the sample is in the range 2.2×10{sup 8}--7.0×10{sup 9} M{sub ⊙} within the central several kiloparsecs subtended by the 15{sup ′′} beam. A method to estimate the size of a CO gas distribution is introduced, which is combined with the total CO flux in the literature. This method is applied to part of our sample, and we find that the median CO radius is 1–4 kpc. From the early stage to the late stage of mergers, we find that the CO size decreases while the median value of the molecular gas mass in the central several-kiloparsec region is constant. Our results statistically support a scenario where molecular gas inflows toward the central region from the outer disk to replenish gas consumed by starburst, and that such a process is common in merging LIRGs.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1973

Water depth estimation with ERTS-1 imagery

Contrast-enhanced 9.5 inch ERTS-1 images were produced for an investigation on ocean water color. Such images lend themselves to water depth estimation by photographic and electronic density contouring. MSS-4 and -5 images of the Great Bahama Bank were density sliced by both methods. Correlation was found between the MSS-4 image and a hydrographic chart at 1:467,000 scale, in a number of areas corresponding to water depth of less than 2 meters, 5 to 10 meters and 10 to about 20 meters. The MSS-5 image was restricted to depths of about 2 meters. Where reflective bottom and clear water are found, ERTS-1 MSS-4 images can be used with density contouring by electronic or photographic methods for estimating depths to 5 meters within about one meter.

Ross, D. S.↗
NASA NTRS1976

A method of distortion pattern synthesis for high response data screening

An empirically derived method of estimating maximum levels of instantaneous inlet total pressure distortion from steady state measurements is presented. The estimation procedure uses steady state total pressure and root mean square turbulent pressure data measurements to synthesize instantaneous distortion patterns. The synthesis method is tailored to intensify distortion patterns in a manner consistent with the characteristics of the particular index to be used in evaluating inlet/engine compatability. The maximum expected value of distortion, a statistically determined function of the length of time of inlet operation, is used to constrain the amount of pattern intensification. Comparison with an independent set of data is presented for verification of the synthesis method.

King, R. W.↗